AI Assists Researchers to Create Radar That Sees Around Corners

Wednesday, July 1, 2020 - 12:49
AI

One of the challenges of designing control systems for autonomous driving cars is anticipating if a pedestrian, bicyclist, or other motorist is about to cross the intended path of the vehicle.

Researchers at the Princeton School of Engineering say they have created an artificial intelligence algorithm that can tease that information out of the background noise associated with ordinary — an inexpensive — radar units, Clean Technica reports.

“This will enable cars to see occluded objects that today’s lidar and camera sensors cannot record, for example, allowing a self-driving vehicle to see around a dangerous intersection” says Felix Heide, an assistant professor of computer science at Princeton and one of researchers. “The radar sensors are also relatively low-cost, especially compared to lidar sensors, and scale to mass production.”

“The algorithms that we developed are highly efficient and fit on current generation automotive hardware systems,” Heide says. “So, you might see this technology already in the next generation of vehicles.”

To permit the system to distinguish objects not visible to optical sensors such as cameras, Heide’s team processed part of the radar signal that standard radars consider background noise rather than usable information. The team applied artificial intelligence techniques to refine the processing and read the images. Fangyin Wei, a graduate student in computer science and one of the paper’s lead authors, said the computer running the system had to learn to recognize cyclists and pedestrians from a very sparse amount of data.

“First we have to detect if something is there. If there is something there, is it important? Is it a cyclist or a pedestrian?” she said. “Then we have to locate it.” Wei said the system currently detects pedestrians and cyclists because the engineers felt those were the most challenging objects because of their small size and varied shape and motion. She said the system could be adjusted to detect vehicles as well.

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